Rating: 4 out of 5 stars
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Ebook13 pages8 minutes
Genetic Algorithms
Rating: 4.5 out of 5 stars
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About this ebook
Examines the application of genetic algorithms in order to solve technical problems. Provides a working case study of a robotic spider and how it can learn to walk without being instructed in physics or explicitly programmed to perform that function.
LanguageEnglish
PublisherIsuru Abeysinghe
Release dateJul 14, 2012
ISBN9781476111032
Author
Isuru Abeysinghe
My life has generally been devoted to the pursuit of technical ambitions, being a graduate of Software Engineering and working for a financial services company as a software developer. However, I have many interests in humanities - history and politics mainly - providing fuel for my creative outlet of writing. I try and integrate equal parts of bleak and almost brutal analysis together with sardonic comedy to produce works that I hope will offer new perspectives and reflect actual social issues in the real world.
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Reviews for Genetic Algorithms
Rating: 4.333333333333333 out of 5 stars
4.5/5
3 ratings1 review
- Rating: 4 out of 5 stars4/5
Sep 2, 2015
A really nice introduction to Genetic Algorithms! Real world examples help you understand the basic concepts of Genetic Algorithms.
Book preview
Genetic Algorithms - Isuru Abeysinghe
INTRODUCTION
Genetic algorithms are a class of algorithms that harness the power of evolutionary mechanics in order to solve a generic class of problem. When a developer is faced with a situation whereby the problem is not clearly defined, or the nature of the problem has the propensity to change over time, the practicality of applying traditional structured logic to engineer a solution is soon eroded. For this reason a programmer needs to develop a system that in itself can learn and adapt when the nature of the problem being solved is ever-changing.
The following are examples of problems that can and have been solved using genetic algorithms:
Handwriting recognition.
Automated vehicles (cars that can follow the road
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